


'''simple docstring'''


def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				while a != 0:
								_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			List[str]							= b % a, a
				return b







def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				if gcd(SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	) != 1:
								_SCREAMING_SNAKE_CASE					:			str							= f"""mod inverse of {a!r} and {m!r} does not exist"""
								raise ValueError(SCREAMING_SNAKE_CASE__	)
				_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			Tuple							= 1, 0, a
				_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			Tuple							= 0, 1, m
				while va != 0:
								_SCREAMING_SNAKE_CASE					:			Any							= ua // va
								_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE						,			_SCREAMING_SNAKE_CASE					:			Optional[Any]							= (ua - q * va), (ua - q * va), (ua - q * va), va, va, va
				return ua % m








'''simple docstring'''


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCAmelCase_						:  int				  =						{'configuration_wavlm': ['WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'WavLMConfig']}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCAmelCase_						:  Tuple				  =						[
				    'WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'WavLMForAudioFrameClassification',
				    'WavLMForCTC',
				    'WavLMForSequenceClassification',
				    'WavLMForXVector',
				    'WavLMModel',
				    'WavLMPreTrainedModel',
				]

if TYPE_CHECKING:
				from .configuration_wavlm import WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP, WavLMConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_wavlm import (
								    WAVLM_PRETRAINED_MODEL_ARCHIVE_LIST,
								    WavLMForAudioFrameClassification,
								    WavLMForCTC,
								    WavLMForSequenceClassification,
								    WavLMForXVector,
								    WavLMModel,
								    WavLMPreTrainedModel,
								)

else:
				import sys

				UpperCAmelCase_						:  Any				  =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




